1. Introduction. Until recently, statistical theory has been restricted to the design and analysis of sampling experiments in which the size and composition of the samples are completely determined before the experimentation begins. The reasons for this are partly historical, dating back to the time when the statistician was consulted , if at all, only after the experiment was over, and partly ...

This work concerns sequential techniques for the canonical blind deconvolution problem in communications signal processing, relating to the estimation of the transmitted (discrete-valued) data sequence from the observed signal at the receiver input, in the presence of unknown linear channel filtering, without recourse to extended training sequences for start-up. This problem has a significant h...

A pest management decision to initiate a control treatment depends upon an accurate estimate of mean pest density. Presence-absence sampling plans significantly reduce sampling efforts to make treatment decisions by using the proportion of infested leaves to estimate mean pest density in lieu of counting individual pests. The use of sequential hypothesis testing procedures can significantly red...

Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from statistics that relate distributions of decisions and response times to diffusion models with time-va...

We present faster overlap tests between spheres and either axis-aligned or oriented boxes. By utilizing quick rejection tests, faster execution times are observed compared to previous techniques. In addition, we present alternative vectorized overlap tests, which are compared to the sequential algorithms. Source code is available online.

In this paper we address the problem of nding the simulated system with the best (maximum or minimum) expected performance when the number of alternatives is nite, but large enough that ranking-and-selection procedures may require too much computation to be practical. Our approach is to use the data provided by the rst stage of sampling in a ranking-and-selection procedure to screen out alterna...

In this paper, we address the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of alternatives is finite, but large enough that ranking-and-selection (R&S) procedures may require too much computation to be practical. Our approach is to use the data provided by the first stage of sampling in an R&S procedure to screen out alternative...

Three hypotheses--the bound-change hypothesis, drift-rate-change hypothesis, and two-stage-processing hypothesis--are proposed to account for data from a perceptual discrimination task in which three different response deadlines were involved and three different payoffs were presented prior to each individual trial. The aim of the present research was to show (1) how the three different hypothe...